Perplexity cost tuning
'Optimize Perplexity costs through model routing, caching, token limits, and budget monitoring.From its SKILL.md
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Perplexity Cost Tuning
Overview
Reduce Perplexity Sonar API costs. Perplexity charges per-token (input + output) plus a per-request fee that varies by search context size. The biggest cost lever is model selection: sonar-pro costs 3-15x more than sonar per request.
Pricing Reference
| Model | Input $/M tokens | Output $/M tokens | Request Fee |
|---|---|---|---|
sonar | $1 | $1 | $5 per 1K requests |
sonar-pro | $3 | $15 | $5 per 1K requests |
sonar-reasoning-pro | $3 | $15 | $5 per 1K requests |
sonar-deep-research | $2 | $8 | $5 per 1K searches |
Search context size (Low/Medium/High) affects the request fee. More context = higher fee.
Prerequisites
- Perplexity API account with usage dashboard
- Understanding of query patterns in your application
- Cache infrastructure for search results
Instructions
Step 1: Route Queries to the Right Model
// 60-70% of queries can use sonar, saving 3-15x per query
function selectModel(query: string): "sonar" | "sonar-pro" {
const simplePatterns = [
/^what is/i, /^define/i, /^who is/i, /^when did/i,
/current price/i, /^how many/i, /^is it true/i,
];
if (simplePatterns.some((p) => p.test(query))) return "sonar";
const complexPatterns = [
/compare.*vs/i, /analysis of/i, /comprehensive/i,
/pros and cons/i, /in-depth/i, /research/i,
];
if (complexPatterns.some((p) => p.test(query))) return "sonar-pro";
return "sonar"; // Default to cheapest
}
Step 2: Limit Output Tokens
set -euo pipefail
# Factual queries need ~100 tokens, not 4096
# Setting max_tokens dramatically reduces output costs
# Simple fact: 100 tokens = $0.0001 output
curl -X POST https://api.perplexity.ai/chat/completions \
-H "Authorization: Bearer $PERPLEXITY_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "sonar",
"messages": [{"role": "user", "content": "Current population of Tokyo"}],
"max_tokens": 100
}'
# Research query: keep at 2048 only when needed
curl -X POST https://api.perplexity.ai/chat/completions \
-H "Authorization: Bearer $PERPLEXITY_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "sonar-pro",
"messages": [{"role": "user", "content": "Compare React vs Vue in 2025 for enterprise apps"}],
"max_tokens": 2048
}'
Step 3: Cache to Eliminate Duplicate Queries
import { LRUCache } from "lru-cache";
import { createHash } from "crypto";
const searchCache = new LRUCache<string, any>({
max: 10000,
ttl: 4 * 3600_000, // 4-hour default TTL
});
async function cachedQuery(query: string, model: string) {
const key = createHash("sha256")
.update(`${model}:${query.toLowerCase().trim()}`)
.digest("hex");
const cached = searchCache.get(key);
if (cached) return cached; // $0 cost
const result = await perplexity.chat.completions.create({
model,
messages: [{ role: "user", content: query }],
});
searchCache.set(key, result);
return result;
}
// Track cache effectiveness
function cacheStats() {
return {
size: searchCache.size,
hitRate: `${((searchCache as any).hits / ((searchCache as any).hits + (searchCache as any).misses) * 100).toFixed(1)}%`,
};
}
Step 4: Use Domain Filters to Reduce Search Cost
set -euo pipefail
# Restricting search domains = less content to process = lower request fee
curl -X POST https://api.perplexity.ai/chat/completions \
-H "Authorization: Bearer $PERPLEXITY_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "sonar",
"messages": [{"role": "user", "content": "Python 3.13 release notes"}],
"search_domain_filter": ["python.org", "docs.python.org"],
"max_tokens": 500
}'
Step 5: Track and Budget
class CostTracker {
private costs: Array<{ model: string; tokens: number; timestamp: Date }> = [];
record(model: string, usage: { total_tokens: number }) {
this.costs.push({
model,
tokens: usage.total_tokens,
timestamp: new Date(),
});
}
dailySummary() {
const today = this.costs.filter(
(c) => c.timestamp.toDateString() === new Date().toDateString()
);
const sonarTokens = today.filter((c) => c.model === "sonar").reduce((s, c) => s + c.tokens, 0);
const proTokens = today.filter((c) => c.model === "sonar-pro").reduce((s, c) => s + c.tokens, 0);
return {
queries: today.length,
estimatedCost: (sonarTokens * 0.000001) + (proTokens * 0.000009), // rough estimate
sonarQueries: today.filter((c) => c.model === "sonar").length,
proQueries: today.filter((c) => c.model === "sonar-pro").length,
};
}
}
Cost Optimization Checklist
- Default model is
sonar(notsonar-pro) -
max_tokensset on every request - Caching enabled for repeated queries
- Model routing by query complexity
- Domain filter used where applicable
- Monthly budget cap set on API key
- Cost tracking in production monitoring
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| High cost per query | Using sonar-pro for everything | Route simple queries to sonar |
| Low cache hit rate | Queries too unique | Normalize queries before hashing |
| Budget exhausted early | No spending caps | Set monthly budget on API key |
| Unexpectedly high bill | No max_tokens limits | Set max_tokens on all requests |
Output
- Model routing saving 60-70% on simple queries
- Token limiting reducing output costs
- Caching eliminating duplicate query costs
- Cost tracking for budget monitoring
Resources
Next Steps
For architecture patterns, see perplexity-reference-architecture.
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